Coherent change detection (CCD) is a technique employed to post-process a set of synthetic aperture radar (SAR) images obtained from substantially the same observation point, to generate a change product. A change product is an image showing changes between successive images of a region of interest. A change product can be useful in two ways. Firstly, it can provide a visual cue to an image analyst as to changes in the region of interest, possibly for further investigation. Secondly, if a change product is expressed as data, it can be used by computer apparatus as the basis for a decision to take a particular action based on the detection of change in a change product image of a region of interest.
CCD is sufficiently accurate to enable detection of subtle changes from one SAR image to the next. For instance, if a region of interest comprises terrain, vehicle tracks imparted in the terrain may be detected in this manner.
However, in certain circumstances, deficiencies may be encountered in a change product. Such deficiencies can include some or all of the following:                Lower resolution than the input SAR images, due to reliance on smoothing;        Significant amounts of speckle;        Smearing of wind-blown clutter;        Long shadows at low grazing angles;        Poor performance around bright reflectors and sidelobes;        Poor signal to noise ratio.        
These deficiencies, if encountered, can reduce the usefulness of a change product. An image generated from a change product would in typical implementations be used by an image analyst, to interpret the change data and from that to make inferences about the observed region of interest. A change product exhibiting some or all of the above deficiencies would have diminished usefulness to an image analyst. The image analyst, using a deficient change product, may be unable to detect and identify relevant change artefacts in a change product. This may unduly affect the efficiency of the image analyst and may require the collection of further image data.
Similar deficiencies to those described for SAR change detection products may also be encountered in SAR imagery. Multilook processing of SAR imagery collected with large changes to the imaging geometry can be used as a mitigation for all of these deficiencies, relying on structure evident in the SAR images to allow registration and alignment to produce a multilook SAR image. This is referred to as multi-aspect multilook processing. However, the standard multilook SAR techniques used hitherto cannot be directly applied to change products, such as CCD, which typically have insufficient statistical correlation to facilitate the required measurements.
Constraining the imaging geometry, so that all the images are collected with a common collection geometry, would allow standard change detection processing to register and align multiple images to produce change detection products that can be combined. However this would only alleviate poor signal to noise ratios leaving the other deficiencies unaltered.